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    [{"authors":null,"categories":null,"content":"I am a Ph.D. student advised by Youngki Lee at the Human-Centered Computer Systems Lab. My research interest lies in building real-time interactable XR systems by designing effective pipelines with recent DNN accelerators.\n","date":1704067200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1704067200,"objectID":"2525497d367e79493fd32b198b28f040","permalink":"","publishdate":"0001-01-01T00:00:00Z","relpermalink":"","section":"authors","summary":"I am a Ph.D. student advised by Youngki Lee at the Human-Centered Computer Systems Lab. My research interest lies in building real-time interactable XR systems by designing effective pipelines with recent DNN accelerators.","tags":null,"title":"Changmin Jeon","type":"authors"},{"authors":null,"categories":null,"content":"Summary Similar to VSense, FallSim is a project that aims to overcome the small size limitation of real-world fall detection datasets with synthetically generated data. However, there are many difficult challenges, so we are still working on it.\nMy Role I am working on this project as a co-author.\n","date":1704067200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1704067200,"objectID":"2ef3ca8322413bfbe67d9d274064b1b2","permalink":"https://changminjeon.com/project/fallsim/","publishdate":"2024-01-01T00:00:00Z","relpermalink":"/project/fallsim/","section":"project","summary":"Enabling real-world fall detection with synthesized fall motions from physics simulations","tags":["On-Going","Sensing"],"title":"FallSim","type":"project"},{"authors":null,"categories":null,"content":"Summary The data of sensors people have to wear is minimal compared to infrastructure-based sensing such as cameras and Wifi. To compensate for this limited sensor data, we propose a method to generate sensor data in a virtual world and perform activity recognition through it. We generate virtual sensor data through Unity, and by applying data augmentation techniques based on motion capture data, we can collect data from various environments. As a result, we improved the performance of Activity Recognition by supplementing the existing limited dataset.\nMy Role I worked on this project as a co-lead. I was responsible for every step, including generating virtual sensor data, building an activity recognition pipeline, and collecting real-world IMU data.\nAccomplishments: Experienced materializing, implementing, and validating ideas through thought and experimentation. Implemented virtual motion synthesis with Unity. Implemented virtual sensor data generation with Unity and Python Implemented activity recognition pipeline with Python using scikit-learn and TensorFlow Real-world IMU data collection with IMU sensor and Arduino board Design and conduct experiments and analyze results ","date":1583020800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1583020800,"objectID":"5a21e59a1b2721e3ced53a426e43fb77","permalink":"https://changminjeon.com/project/vsense/","publishdate":"2020-03-01T00:00:00Z","relpermalink":"/project/vsense/","section":"project","summary":"Overcoming small size limitation of real-world activity recognition datasets with synthetically generated data","tags":["Sensing"],"title":"VSense","type":"project"},{"authors":null,"categories":null,"content":"Summary ODLIA is an optimization - deep learning integrated acceleration system aiming to achieve highly fast (\u0026lt;10ms) XR scene understanding. Among the various scene-understanding techniques, we are focusing on Hand-Object Tracking.\nMy Role As the team lead, I am responsible for all aspects.\n","date":1704067200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1704067200,"objectID":"1baf347754a0a129461391f39593f4d0","permalink":"https://changminjeon.com/project/odlia/","publishdate":"2024-01-01T00:00:00Z","relpermalink":"/project/odlia/","section":"project","summary":"Optimization - deep learning integrated acceleration system for real-time XR scene understanding","tags":["On-Going","On-Device AI"],"title":"ODLIA","type":"project"},{"authors":null,"categories":null,"content":"Summary Band is the first mobile inference platform to support multi-DNN workloads on heterogeneous mobile processors. Existing mobile deep learning frameworks such as TFLite focus on single DNN inference and thus cannot fully handle multi-DNN workloads with heterogeneous processors. Moreover, the limited operator support of different accelerators further complicates the problem. Band tackles this challenge by partitioning DNNs into subgraphs, dynamically selecting optimal schedules, and considering fallback operators for unsupported processors. Evaluation results show that Band outperforms TensorFlow Lite by up to 5.04× for single-app multi-DNN workloads and achieves a 3.76× higher satisfaction rate for latency-critical multi-app scenarios.\nWith novel findings and extensive evaluation, Band was published in MobiSys 2022.\nMy Role Our team consisted of 5 people, and we implemented and evaluated the entire platform together. Furthermore, I designed and implemented the subgraph partitioning algorithm, which is the core concept of Band.\nAccomplishments: Implemented Band in a 5-person team and experienced collaboration, including code review and testing Implemented Band based on well-organized TensorFlow Lite C++ code, increasing my understanding of system design and C++-based development Designed and implemented techniques based on system profiling Gained an understanding of accelerator APIs such as OpenCL and NNAPI while implementing a platform that supports heterogeneous processors ","date":1656288000,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1656288000,"objectID":"1c0f9279892afef2ea3d24a3cd254811","permalink":"https://changminjeon.com/project/band/","publishdate":"2022-06-27T00:00:00Z","relpermalink":"/project/band/","section":"project","summary":"Multi-DNN inference framework for heterogeneous mobile processors with subgraph-level scheduling","tags":["On-Device AI"],"title":"Band","type":"project"},{"authors":null,"categories":null,"content":"Summary Mondrian is an edge system that enables high-performance object detection on high-resolution video streams. Different objects have highly diverse object detection difficulties within a single image due to their varying appearance. Still, existing edge video analytics systems are limited to extracting ROIs (Region of Interest). Mondrian not only extracts ROI regions but also reduces the amount of computation through ROI scaling according to each ROI’s difficulty and effectively performs object detection through Packed Inference with varying ROI sizes. Mondrian achieves 2.5 times higher throughput through its compressive packed inference technique than SOTA edge video analytics systems.\nMy Role As the team lead, I am responsible for all aspects. Since the existing video analytics systems are based on Python, I implemented the entire system from scratch in C++.\nAccomplishments: Implemented the entire video analytics system from scratch in C++ Implemented C++-based memory management Implemented C++ image processing using OpenCV Became more familiar with code reviews by working in a two-person development team Implemented an automated mobile experiment toolkit using Python ","date":1704067200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1704067200,"objectID":"51c234b19ae3a204114c39c8d559875b","permalink":"https://changminjeon.com/project/mondrian/","publishdate":"2024-01-01T00:00:00Z","relpermalink":"/project/mondrian/","section":"project","summary":"On-device high-throughput video analytics on mobile devices with compressive packed inference","tags":["On-Device AI"],"title":"Mondrian","type":"project"},{"authors":[],"categories":null,"content":" Click on the Slides button above to view the built-in slides feature. Slides can be added in a few ways:\nCreate slides using Hugo Blox Builder’s Slides feature and link using slides parameter in the front matter of the talk file Upload an existing slide deck to static/ and link using url_slides parameter in the front matter of the talk file Embed your slides (e.g. Google Slides) or presentation video on this page using shortcodes. Further event details, including page elements such as image galleries, can be added to the body of this page.\n","date":1906549200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1906549200,"objectID":"a8edef490afe42206247b6ac05657af0","permalink":"https://changminjeon.com/talk/example-talk/","publishdate":"2017-01-01T00:00:00Z","relpermalink":"/talk/example-talk/","section":"event","summary":"An example talk using Hugo Blox Builder's Markdown slides feature.","tags":[],"title":"Example Talk","type":"event"},{"authors":["Changmin Jeon","Seonjun Kim","Juheon Yi","Youngki Lee"],"categories":null,"content":" ","date":1704067200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1704067200,"objectID":"970b2ab52aca2bab98cd066084891034","permalink":"https://changminjeon.com/publication/mondrian/","publishdate":"2017-01-01T00:00:00Z","relpermalink":"/publication/mondrian/","section":"publication","summary":" ","tags":["On-Device AI"],"title":"Mondrian: On-Device High-Performance Video Analytics with Compressive Packed Inference","type":"publication"},{"authors":null,"categories":null,"content":"from IPython.core.display import Image Image(\u0026#39;https://www.python.org/static/community_logos/python-logo-master-v3-TM-flattened.png\u0026#39;) print(\u0026#34;Welcome to Academic!\u0026#34;) Welcome to Academic! Organize your notebooks Place the notebooks that you would like to publish in a notebooks folder at the root of your website.\nImport the notebooks into your site pipx install academic academic import \u0026#39;notebooks/**.ipynb\u0026#39; content/post/ --verbose The notebooks will be published to the folder you specify above. In this case, they will be published to your content/post/ folder.\n","date":1699056000,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1699056000,"objectID":"94fa5e486d3bf3e0941e2ff6e7126c06","permalink":"https://changminjeon.com/post/blog-with-jupyter/","publishdate":"2023-11-04T00:00:00Z","relpermalink":"/post/blog-with-jupyter/","section":"post","summary":"Easily blog from Jupyter notebooks!","tags":null,"title":"Blog with Jupyter Notebooks!","type":"post"},{"authors":["Joo Seong Jeong","Jingyu Lee","Donghyun Kim","Changmin Jeon","Changjin Jeong","Youngki Lee","Byung-Gon Chun"],"categories":null,"content":" ","date":1656288000,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1656288000,"objectID":"504efe7d2c15aecc78b16244e3650476","permalink":"https://changminjeon.com/publication/band/","publishdate":"2017-01-01T00:00:00Z","relpermalink":"/publication/band/","section":"publication","summary":" ","tags":["On-Device AI"],"title":"Band: Coordinated Multi-DNN Inference on Heterogeneous Mobile Processors","type":"publication"},{"authors":["Changmin Jeon","吳恩達"],"categories":["Demo","教程"],"content":"import libr print(\u0026#39;hello\u0026#39;) Overview The Wowchemy website builder for Hugo, along with its starter templates, is designed for professional creators, educators, and teams/organizations - although it can be used to create any kind of site The template can be modified and customised to suit your needs. It’s a good platform for anyone looking to take control of their data and online identity whilst having the convenience to start off with a no-code solution (write in Markdown and customize with YAML parameters) and having flexibility to later add even deeper personalization with HTML and CSS You can work with all your favourite tools and apps with hundreds of plugins and integrations to speed up your workflows, interact with your readers, and much more Get Started 👉 Create a new site 📚 Personalize your site 💬 Chat with the Wowchemy community or Hugo community 🐦 Twitter: @wowchemy @GeorgeCushen #MadeWithWowchemy 💡 Request a feature or report a bug for Wowchemy ⬆️ Updating Wowchemy? View the Update Tutorial and Release Notes Crowd-funded open-source software To help us develop this template and software sustainably under the MIT license, we ask all individuals and businesses that use it to help support its ongoing maintenance and development via sponsorship.\n❤️ Click here to become a sponsor and help support Wowchemy’s future ❤️ As a token of appreciation for sponsoring, you can unlock these awesome rewards and extra features 🦄✨\nEcosystem Hugo Academic CLI: Automatically import publications from BibTeX Inspiration Check out the latest demo of what you’ll get in less than 10 minutes, or view the showcase of personal, project, and business sites.\nFeatures Page builder - Create anything with widgets and elements Edit any type of content - Blog posts, publications, talks, slides, projects, and more! Create content in Markdown, Jupyter, or RStudio Plugin System - Fully customizable color and font themes Display Code and Math - Code highlighting and LaTeX math supported Integrations - Google Analytics, Disqus commenting, Maps, Contact Forms, and more! Beautiful Site - Simple and refreshing one page design Industry-Leading SEO - Help get your website found on search engines and social media Media Galleries - Display your images and videos with captions in a customizable gallery Mobile Friendly - Look amazing on every screen with a mobile friendly version of your site Multi-language - 34+ language packs including English, 中文, and Português Multi-user - Each author gets their own profile page Privacy Pack - Assists with GDPR Stand Out - Bring your site to life with animation, parallax backgrounds, and scroll effects One-Click Deployment - No servers. No databases. Only files. Themes Wowchemy and its templates come with automatic day (light) and night (dark) mode built-in. Alternatively, visitors can choose their preferred mode - click the moon icon in the top right of the Demo to see it in action! Day/night mode can also be disabled by the site admin in params.toml.\nChoose a stunning theme and font for your site. Themes are fully customizable.\nLicense Copyright 2016-present George Cushen.\nReleased under the MIT license.\n","date":1607817600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1607817600,"objectID":"279b9966ca9cf3121ce924dca452bb1c","permalink":"https://changminjeon.com/post/getting-started/","publishdate":"2020-12-13T00:00:00Z","relpermalink":"/post/getting-started/","section":"post","summary":"Welcome 👋 We know that first impressions are important, so we've populated your new site with some initial content to help you get familiar with everything in no time.","tags":["Academic","开源"],"title":"Welcome to Hugo Blox Builder, the website builder for Hugo","type":"post"},{"authors":null,"categories":null,"content":"Hugo Blox Builder is designed to give technical content creators a seamless experience. You can focus on the content and Wowchemy handles the rest.\nHighlight your code snippets, take notes on math classes, and draw diagrams from textual representation.\nOn this page, you’ll find some examples of the types of technical content that can be rendered with Wowchemy.\nExamples Code Wowchemy supports a Markdown extension for highlighting code syntax. You can customize the styles under the syntax_highlighter option in your config/_default/params.yaml file.\n```python import pandas as pd data = pd.read_csv(\u0026#34;data.csv\u0026#34;) data.head() ``` renders as\nimport pandas as pd data = pd.read_csv(\u0026#34;data.csv\u0026#34;) data.head() Mindmaps Wowchemy supports a Markdown extension for mindmaps.\nSimply insert a Markdown markmap code block and optionally set the height of the mindmap as shown in the example below.\nA simple mindmap defined as a Markdown list:\n```markmap {height=\u0026#34;200px\u0026#34;} - Hugo Modules - wowchemy - blox-plugins-netlify - blox-plugins-netlify-cms - blox-plugins-reveal ``` renders as\n- Hugo Modules - wowchemy - blox-plugins-netlify - blox-plugins-netlify-cms - blox-plugins-reveal A more advanced mindmap with formatting, code blocks, and math:\n```markmap - Mindmaps - Links - [Wowchemy Docs](https://docs.hugoblox.com/) - [Discord Community](https://discord.gg/z8wNYzb) - [GitHub](https://github.com/HugoBlox/hugo-blox-builder) - Features - Markdown formatting - **inline** ~~text~~ *styles* - multiline text - `inline code` - ```js console.log(\u0026#39;hello\u0026#39;); console.log(\u0026#39;code block\u0026#39;); ``` - Math: $x = {-b \\pm \\sqrt{b^2-4ac} \\over 2a}$ ``` renders as\n- Mindmaps - Links - [Wowchemy Docs](https://docs.hugoblox.com/) - [Discord Community](https://discord.gg/z8wNYzb) - [GitHub](https://github.com/HugoBlox/hugo-blox-builder) - Features - Markdown formatting - **inline** ~~text~~ *styles* - multiline text - `inline code` - ```js console.log(\u0026#39;hello\u0026#39;); console.log(\u0026#39;code block\u0026#39;); ``` - Math: $x = {-b \\pm \\sqrt{b^2-4ac} \\over 2a}$ Charts Wowchemy supports the popular Plotly format for interactive charts.\nSave your Plotly JSON in your page folder, for example line-chart.json, and then add the {{\u0026lt; chart data=\u0026#34;line-chart\u0026#34; \u0026gt;}} shortcode where you would like the chart to appear.\nDemo:\nYou might also find the Plotly JSON Editor useful.\nMath Wowchemy supports a Markdown extension for $\\LaTeX$ math. You can enable this feature by toggling the math option in your config/_default/params.yaml file.\nTo render inline or block math, wrap your LaTeX math with {{\u0026lt; math \u0026gt;}}$...${{\u0026lt; /math \u0026gt;}} or {{\u0026lt; math \u0026gt;}}$$...$${{\u0026lt; /math \u0026gt;}}, respectively. (We wrap the LaTeX math in the Wowchemy math shortcode to prevent Hugo rendering our math as Markdown. The math shortcode is new in v5.5-dev.)\nExample math block:\n{{\u0026lt; math \u0026gt;}} $$ \\gamma_{n} = \\frac{ \\left | \\left (\\mathbf x_{n} - \\mathbf x_{n-1} \\right )^T \\left [\\nabla F (\\mathbf x_{n}) - \\nabla F (\\mathbf x_{n-1}) \\right ] \\right |}{\\left \\|\\nabla F(\\mathbf{x}_{n}) - \\nabla F(\\mathbf{x}_{n-1}) \\right \\|^2} $$ {{\u0026lt; /math \u0026gt;}} renders as\n$$\\gamma_{n} = \\frac{ \\left | \\left (\\mathbf x_{n} - \\mathbf x_{n-1} \\right )^T \\left [\\nabla F (\\mathbf x_{n}) - \\nabla F (\\mathbf x_{n-1}) \\right ] \\right |}{\\left \\|\\nabla F(\\mathbf{x}_{n}) - \\nabla F(\\mathbf{x}_{n-1}) \\right \\|^2}$$ Example inline math {{\u0026lt; math \u0026gt;}}$\\nabla F(\\mathbf{x}_{n})${{\u0026lt; /math \u0026gt;}} renders as $\\nabla F(\\mathbf{x}_{n})$.\nExample multi-line math using the math linebreak (\\\\):\n{{\u0026lt; math \u0026gt;}} $$f(k;p_{0}^{*}) = \\begin{cases}p_{0}^{*} \u0026amp; \\text{if }k=1, \\\\ 1-p_{0}^{*} \u0026amp; \\text{if }k=0.\\end{cases}$$ {{\u0026lt; /math \u0026gt;}} renders as\n$$ f(k;p_{0}^{*}) = \\begin{cases}p_{0}^{*} \u0026amp; \\text{if }k=1, \\\\ 1-p_{0}^{*} \u0026amp; \\text{if }k=0.\\end{cases} $$ Diagrams Wowchemy supports a Markdown extension for diagrams. You can enable this feature by toggling the diagram option in your config/_default/params.toml file or by adding diagram: true to your page front matter.\nAn example flowchart:\n```mermaid graph TD A[Hard] --\u0026gt;|Text| B(Round) B --\u0026gt; C{Decision} C --\u0026gt;|One| D[Result 1] C --\u0026gt;|Two| E[Result 2] ``` renders as\ngraph TD A[Hard] --\u0026gt;|Text| B(Round) B --\u0026gt; C{Decision} C --\u0026gt;|One| D[Result 1] C --\u0026gt;|Two| E[Result 2] An example sequence diagram:\n```mermaid sequenceDiagram Alice-\u0026gt;\u0026gt;John: Hello John, how are you? loop Healthcheck John-\u0026gt;\u0026gt;John: Fight against hypochondria end Note right of John: Rational thoughts! John--\u0026gt;\u0026gt;Alice: Great! John-\u0026gt;\u0026gt;Bob: How about you? Bob--\u0026gt;\u0026gt;John: Jolly good! ``` renders as\nsequenceDiagram Alice-\u0026gt;\u0026gt;John: Hello John, how are you? loop Healthcheck John-\u0026gt;\u0026gt;John: Fight against hypochondria end Note right of John: Rational thoughts! John--\u0026gt;\u0026gt;Alice: Great! John-\u0026gt;\u0026gt;Bob: How about you? Bob--\u0026gt;\u0026gt;John: Jolly good! An example Gantt diagram:\n```mermaid gantt section Section Completed :done, des1, 2014-01-06,2014-01-08 Active :active, des2, 2014-01-07, 3d Parallel 1 : des3, after des1, 1d Parallel 2 : des4, after des1, 1d Parallel 3 : des5, after des3, 1d Parallel 4 : des6, after des4, 1d ``` renders as\ngantt section …","date":1562889600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1562889600,"objectID":"07e02bccc368a192a0c76c44918396c3","permalink":"https://changminjeon.com/post/writing-technical-content/","publishdate":"2019-07-12T00:00:00Z","relpermalink":"/post/writing-technical-content/","section":"post","summary":"Hugo Blox Builder is designed to give technical content creators a seamless experience. You can focus on the content and Wowchemy handles the rest.\nHighlight your code snippets, take notes on math classes, and draw diagrams from textual representation.","tags":null,"title":"Writing technical content in Markdown","type":"post"},{"authors":[],"categories":[],"content":"Create slides in Markdown with Hugo Blox Builder Hugo Blox Builder | Documentation\nFeatures Efficiently write slides in Markdown 3-in-1: Create, Present, and Publish your slides Supports speaker notes Mobile friendly slides Controls Next: Right Arrow or Space Previous: Left Arrow Start: Home Finish: End Overview: Esc Speaker notes: S Fullscreen: F Zoom: Alt + Click PDF Export Code Highlighting Inline code: variable\nCode block:\nporridge = \u0026#34;blueberry\u0026#34; if porridge == \u0026#34;blueberry\u0026#34;: print(\u0026#34;Eating...\u0026#34;) Math In-line math: $x + y = z$\nBlock math:\n$$ f\\left( x \\right) = ;\\frac{{2\\left( {x + 4} \\right)\\left( {x - 4} \\right)}}{{\\left( {x + 4} \\right)\\left( {x + 1} \\right)}} $$\nFragments Make content appear incrementally\n{{% fragment %}} One {{% /fragment %}} {{% fragment %}} **Two** {{% /fragment %}} {{% fragment %}} Three {{% /fragment %}} Press Space to play!\nOne Two Three A fragment can accept two optional parameters:\nclass: use a custom style (requires definition in custom CSS) weight: sets the order in which a fragment appears Speaker Notes Add speaker notes to your presentation\n{{% speaker_note %}} - Only the speaker can read these notes - Press `S` key to view {{% /speaker_note %}} Press the S key to view the speaker notes!\nOnly the speaker can read these notes Press S key to view Themes black: Black background, white text, blue links (default) white: White background, black text, blue links league: Gray background, white text, blue links beige: Beige background, dark text, brown links sky: Blue background, thin dark text, blue links night: Black background, thick white text, orange links serif: Cappuccino background, gray text, brown links simple: White background, black text, blue links solarized: Cream-colored background, dark green text, blue links Custom Slide Customize the slide style and background\n{{\u0026lt; slide background-image=\u0026#34;/media/boards.jpg\u0026#34; \u0026gt;}} {{\u0026lt; slide background-color=\u0026#34;#0000FF\u0026#34; \u0026gt;}} {{\u0026lt; slide class=\u0026#34;my-style\u0026#34; \u0026gt;}} Custom CSS Example Let’s make headers navy colored.\nCreate assets/css/reveal_custom.css with:\n.reveal section h1, .reveal section h2, .reveal section h3 { color: navy; } Questions? Ask\nDocumentation\n","date":1549324800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1549324800,"objectID":"0e6de1a61aa83269ff13324f3167c1a9","permalink":"https://changminjeon.com/slides/example/","publishdate":"2019-02-05T00:00:00Z","relpermalink":"/slides/example/","section":"slides","summary":"An introduction to using Hugo Blox Builder's Slides feature.","tags":[],"title":"Slides","type":"slides"},{"authors":null,"categories":null,"content":"SNU \u0026amp; LG Data Science Course: Machine Learning Machine Learning Theory and Practice Textbook : An Introduction to Statistical Learning Jan 2024, Jan 2023, Jan 2022, Jan 2021, Feb 2020 SNU \u0026amp; Samsung Data Science Course: Machine Learning Machine Learning Theory and Practice Textbook : An Introduction to Statistical Learning Jul 2023, Mar 2023, Mar 2022, Aug 2021, Feb 2021, Aug 2020, Feb 2020 SNU \u0026amp; Samsung Data Science Course: Machine Learning Projects Machine Learning Projects with Kaggle Oct 2023, Jun 2023 SNU \u0026amp; SK Hynix ML Engineer Course: Time Series Data Analysis Time Series Data Analysis Linear \u0026amp; Non-Linear Time-Series Models Hidden Markov Model Filtering Methods Deep Learning Models Nov 2022, Aug 2022 SNU Big Data \u0026amp; Fintech Expert Training Course: Fintech Industry Application Mobile Deep Learning \u0026amp; Machine Learning Application Development 2021 Apr SNU : Computer Programming (M1522.000600, 001) Object Oriented Programming in Java \u0026amp; C++ Fall 2020 SNU : Mobile and Ubiquitous Computing (M1522.003300, 001) Mobile Computing Activity recognition Indoor and outdoor localization Health care Mobile power optimization Mobile cloud and edge systems Spring 2020 ","date":1530140400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1530140400,"objectID":"f3c9d28fb9eb50176b452b4ff319a2f9","permalink":"https://changminjeon.com/teachings/","publishdate":"2018-06-28T00:00:00+01:00","relpermalink":"/teachings/","section":"","summary":"SNU \u0026 LG Data Science Course: Machine Learning Machine Learning Theory and Practice Textbook : An Introduction to Statistical Learning Jan 2024, Jan 2023, Jan 2022, Jan 2021, Feb 2020 SNU \u0026 Samsung Data Science Course: Machine Learning Machine Learning Theory and Practice Textbook : An Introduction to Statistical Learning Jul 2023, Mar 2023, Mar 2022, Aug 2021, Feb 2021, Aug 2020, Feb 2020 SNU \u0026 Samsung Data Science Course: Machine Learning Projects Machine Learning Projects with Kaggle Oct 2023, Jun 2023 SNU \u0026 SK Hynix ML Engineer Course: Time Series Data Analysis Time Series Data Analysis Linear \u0026 Non-Linear Time-Series Models Hidden Markov Model Filtering Methods Deep Learning Models Nov 2022, Aug 2022 SNU Big Data \u0026 Fintech Expert Training Course: Fintech Industry Application Mobile Deep Learning \u0026 Machine Learning Application Development 2021 Apr SNU : Computer Programming (M1522.","tags":null,"title":"Teachings","type":"page"}]